Evidence map›Paper›PMID 42290867›Full record

ArticleFrontiers in endocrinology2026

Development and validation of a simplified pre-screening model for diabetic foot ulcer identification in diabetic patients.

Weidi Wang, Yue Guo, Sining Chen, Wenshi Ou, Qiaoyi Wu

Abstract readValidation Study
In one paragraph

Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Weidi Wang *Trauma Center and Emergency Surgery Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Yue Guo *Trauma Center and Emergency Surgery Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Sining Chen *Trauma Center and Emergency Surgery Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Wenshi Ou *Hepatopancreatobiliary Surgery Department, the First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Qiaoyi WuTrauma Center and Emergency Surgery Department, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aimed to develop a simplified cross-sectional pre-screening tool for diabetic foot ulcer (DFU) using routinely available clinical indicators, with particular focus on the albumin-to-glycated hemoglobin ratio (Alb/HbA1c) as a composite marker of nutritional status and glycemic control. Methods: We retrospectively analyzed 1,854 hospitalized patients with type 2 diabetes (training set, January 2012-December 2020) and 678 outpatients (validation set, January 2021-December 2025) from a geographically distinct branch of the same hospital system. Demographic characteristics, lifestyle factors, and laboratory parameters were collected. LASSO regression and multivariate logistic regression were used for predictor selection. Model performance was assessed by area under the curve (AUC), calibration curves, Hosmer-Lemeshow test, and Brier score. Risk was visualized using nomograms and heatmaps. Results: DFU prevalence was 20.9% in the training set and 15.8% in the validation set. Four independent predictors were identified: age (OR = 1.029/year), history of injury (OR = 7.57), alcohol consumption (OR = 0.48, see Discussion for interpretation), and Alb/HbA1c ratio (OR = 0.49). The model showed good discrimination in the training (AUC 0.807, 95% CI 0.790-0.825) and validation sets (AUC 0.817, 95% CI 0.782-0.852), with acceptable calibration (Hosmer-Lemeshow P > 0.05; Brier scores 0.127 and 0.118). Internal validation confirmed stability (optimism-corrected AUC = 0.803). Risk heatmaps revealed synergistic interactions between age and Alb/HbA1c, with injury history amplifying risk across all strata. Conclusion: This simplified pre-screening model using age, injury history, alcohol consumption, and Alb/HbA1c demonstrates a high negative predictive value, making it suitable for ruling out DFU in resource-limited primary care settings.

Indexed as

Diabetes Mellitus, Type 2Diabetic FootAgedBiomarkersCross-Sectional StudiesFemaleGlycated HemoglobinHumansMaleMass ScreeningMiddle AgedRetrospective StudiesRisk FactorsSerum AlbuminBiomarkersGlycated Hemoglobinhemoglobin A1c protein, humanSerum Albuminalbumincross-sectional risk identificationdiabetic foot ulcerhistory of injurynutritional status

Identifiers

PMID42290867
PMCPMC13259758

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.